Evidence map›Paper›PMID 31504306›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2020

Citywide Transmission of Multidrug-resistant Tuberculosis Under China's Rapid Urbanization: A Retrospective Population-based Genomic Spatial Epidemiological Study.

Qi Jiang, Qingyun Liu, Lecai Ji, Jinli Li, Yaling Zeng, Liangguang Meng, Geyang Luo, Chongguang Yang, Howard E Takiff, Zheng Yang and 3 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

62 citing papers in PubMed.

  1. Quantifying the community transmission ofEmerging microbes & infections · 2026
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  11. Extensive Endemic Transmission of Multidrug-ResistantOpen forum infectious diseases · 2026
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2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Qi JiangShenzhen Center for Chronic Disease Control, Shenzhen, China.
Qingyun LiuShenzhen Center for Chronic Disease Control, Shenzhen, China.
Lecai JiShenzhen Center for Chronic Disease Control, Shenzhen, China.
Jinli LiShenzhen Center for Chronic Disease Control, Shenzhen, China.
Yaling ZengShenzhen Center for Chronic Disease Control, Shenzhen, China.
Liangguang MengShenzhen Center for Chronic Disease Control, Shenzhen, China.
Geyang LuoKey Laboratory of Medical Molecular Virology (Ministry of Education,National Health Commission, Chinese Academy of Medical Sciences), School of Basic Medical Sciences, Shanghai Medical College and Shanghai Public Health Clinical Center, Fudan University, Shenzhen, China.
Chongguang YangSchool of Public Health, Yale University, New Haven, Connecticut, USA.
Howard E TakiffIntegrated Mycobacterial Pathogenomics Unit, Institut Pasteur, Paris, France.
Zheng YangShenzhen Center for Chronic Disease Control, Shenzhen, China.
Weiguo TanShenzhen Center for Chronic Disease Control, Shenzhen, China.
Weiye YuShenzhen Center for Chronic Disease Control, Shenzhen, China.
Qian GaoShenzhen Center for Chronic Disease Control, Shenzhen, China.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

backgroundPopulation movement could extend multidrug-resistant tuberculosis (MDR-TB) transmission and complicate its global prevalence. We sought to identify the high-risk populations and geographic sites of MDR-TB transmission in Shenzhen, the most common destination for internal migrants in China.

methodsWe performed a population-based, retrospective study in patients diagnosed with MDR-TB in Shenzhen during 2013-2017. By defining genomic clusters with a threshold of 12-single-nucleotide polymorphism distance based on whole-genome sequencing of their clinical strains, the clustering rate was calculated to evaluate the level of recent transmission. Risk factors were identified by multivariable logistic regression. To further delineate the epidemiological links, we invited the genomic-clustered patients to an in-depth social network investigation.

resultsIn total, 105 (25.2%) of the 417 enrolled patients with MDR-TB were grouped into 40 genome clusters, suggesting recent transmission of MDR strains. The adjusted risk for student to have a clustered strain was 4.05 (95% confidence interval, 1.06-17.0) times greater than other patients. The majority (70%, 28/40) of the genomic clusters involved patients who lived in different districts, with residences separated by an average of 8.76 kilometers. Other than household members, confirmed epidemiological links were also identified among classmates and workplace colleagues.

conclusionsThese findings demonstrate that local transmission of MDR-TB is a serious problem in Shenzhen. While most transmission occurred between people who lived distant from each other, there was clear evidence that transmission occurred in schools and workplaces, which should be included as targeted sites for active case finding.The average residential distance between genomic-clustered cases was more than 8 kilometers, while schools and workplaces, identified as sites of transmission in this study, deserve increased vigilance for targeted case finding of multidrug-resistant tuberculosis.

Indexed as

Mycobacterium tuberculosisTuberculosis, Multidrug-ResistantAntitubercular AgentsChinaGenomicsHumansRetrospective StudiesUrbanizationAntitubercular Agentsinternal migrantsmultidrug-resistant tuberculosisspatial analysistransmissionwhole-genome sequencing

Identifiers

PMID31504306
PMCPMC8127054

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.